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iplookup

by io.github.pipeworx-io

Send Pipeworx Feedback

pipeworx_feedback

Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a claim_token; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNobug = something broke or returned wrong data. feature = a new tool or capability you wish existed. data_gap = data Pipeworx does not currently expose. praise = positive note. other = anything else.
contextNoOptional structured context: which tool, pack, or vertical this relates to.
messageNoYour feedback in plain text. Be specific (which tool, what error, what data was missing). 1-2 sentences typical, 2000 chars max.
claim_tokenNoRead the reply to a report you filed earlier: pass the `pwfb_…` token that filing returned, with no other arguments. Returns the status and, once resolved, what actually changed.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • addedInput schema / properties / claim_token
      Added value: +{
+  "description": "Read the reply to a report you filed earlier: pass the `pwfb_…` token that filing returned, with no other arguments. Returns the status and, once resolved, what actually changed.",
+  "type": "string"
+}
    • removedInput schema / required
      Removed value: -[
-  "type",
-  "message"
-]
  2. Added

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations are all false, so the description carries the burden. It discloses rate limiting ('Rate-limited to 5 per identifier per day'), the claim_token mechanism for later status checks, that the team reads digests daily, and that it's free. It also warns against pasting end-user prompts, adding practical behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Every sentence earns its place. The description is front-loaded with purpose, lists use cases, gives exclusions, explains token behavior, and ends with rate limits and cost. Though long, it is tightly structured with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a feedback tool with nested context objects and no output schema, the description covers all necessary behavior: how to describe issues, token-based follow-up, rate limits, and cost. It also aligns with the sibling-tool landscape by clearly separating from ask_pipeworx and other servers' feedback mechanisms.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds value by clarifying message content ('Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt') and showing claim_token usage syntax ('pipeworx_feedback({claim_token:"pwfb_…"})'). This goes beyond the schema, justifying a 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly defines the tool's purpose: to send feedback to the Pipeworx team about broken, missing, or needed functionality. It distinguishes from siblings by explicitly limiting scope to Pipeworx connection tools and categorizing feedback types (bug, feature, data_gap, praise).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use guidance: 'Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise).' It also gives a clear exclusion: 'if the tool came from a different MCP server . . . file it with that server instead.'

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.9/5.0
Disambiguation2/5

Several tool groups have unclear boundaries: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, polymarket_edges/arbitrage/bet_research overlap heavily, and scan_competitor_ai_presence merely wraps ai_visibility_check. An agent would frequently have to guess which of several overlapping tools to call.

Naming Consistency3/5

Most tools use lowercase snake_case, but the set mixes verb-first names (resolve_entity, validate_claim) with noun/service-first compounds (polymarket_edges, pipeworx_trending, ai_visibility_check) and inconsistent suffix semantics (ask_pipeworx_beta vs ask_pipeworx_grounded). The pattern is readable but not predictable.

Tool Count2/5

33 tools is far too many for a server named iplookup; only 2 of 33 relate to IP geolocation. The rest form a sprawling data/prediction-market/memory platform that would be better split into multiple focused servers.

Completeness4/5

Within the actual described scope (a Pipeworx data platform), coverage is strong: routed lookups, grounded verification, deep research, entity identity/profile/comparison, claim validation, discovery, subscriptions, memory, feedback, trending, and a full prediction-market arbitrage suite. Minor gaps exist (no direct pack-listing tool, no update for memory values), but there are no critical dead ends.

Resources